Opto-Electronic Engineering, Volume. 51, Issue 11, 240220-1(2024)
A solar cell defect detection model optimized and improved based on YOLOv8
[1] Z R Peng, H S Xu, S P Xiao. A CatBoost optimization-based fault diagnosis model for photovoltaic arrays. Acta Electron Sin, 52, 2418-2428(2024).
[2] Y T Shi, F Dai, C M Yang. Defect detection of solar photovoltaic cell. J Electron Meas Instrum, 34, 157-164(2020).
[3] K Bedrich, M Bokalič, M Bliss et al. Electroluminescence imaging of PV devices: advanced vignetting calibration. IEEE J Photovoltaics, 8, 1297-1304(2018).
[4] X Chen, T Karin, A Jain. Automated defect identification in electroluminescence images of solar modules. Solar Energy, 242, 20-29(2022).
[5] Z R Peng, Y Q Zhang, S P Xiao. Research on surface defect detection of solar cell with improved YOLOv5 algorithm. Acta Energ Sol Sin, 45, 368-375(2024).
[6] S Q Ren, K M He, R Girshick et al. Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell, 39, 1137-1149(2017).
[7] S T Pei, H Y Zhang, C L Hu et al. The defect detection method for cross-environment power transmission line based on ER-YOLO algorithm. Trans China Electrotech Soc, 39, 2825-2840(2024).
[8] X L Qian, H Q Zhang, H L Zhang et al. Solar cell surface defect detection based on visual saliency. Chin J Sci Instrum, 38, 1570-1578(2017).
[9] D M Tsai, S C Wu, W C Li. Defect detection of solar cells in electroluminescence images using Fourier image reconstruction. Solar Energy Mater Solar Cells, 99, 250-262(2012).
[10] L Liu, C Wang, S W Zhao et al. Research on solar cells defect detection technology based on machine vision. J Electron Meas Instrum, 32, 47-52(2018).
[12] W B Zhang, Y H Ma, X J Bai et al. Defect identification of solar panels using improved Faster R-CNN. Power Syst Technol, 46, 2593-2600(2022).
[13] S Lu, K X Wu, J X Chen. Solar cell surface defect detection based on optimized YOLOv5. IEEE Access, 11, 71026-71036(2023).
[14] Q C Zhou, B C Wang. Solar cell surface defect detection based on improved YOLOv7. J Comput Appl, 43, 223-228(2023).
[15] H Fu, G Q Cheng. Convolutional neural network based efficient detector for multicrystalline photovoltaic cells defect detection. Energy Sources Part A Recovery Util Environ Eff, 45, 8686-8702(2023).
[16] Y Zhang, B T Li, J H Shang et al. Defect detection of transmission line damper based on multi-scale convolutional attention mechanism. Trans China Electrotech Soc, 39, 3522-3537(2024).
[17] Z Wang, Z X Hua, Y C Wen et al. E-YOLO: recognition of estrus cow based on improved YOLOv8n model. Expert Syst Appl, 238, 122212(2024).
[19] H J Liu, L S Liu, M C Zhang. An improved infrared object detection algorithm based on YOLOv5. Laser Technol, 48, 534-541(2024).
[20] R M Zhang, Y F Xiao, Z N Jia et al. Improved YOLOv7 algorithm for target detection in complex environments from UAV perspective. Opto-Electron Eng, 51, 240051(2024).
[21] P F Wang, Y T Li, Y Y Huang et al. Defects detection for cable surface of cable-stayed bridge based on improved YOLOv5s network. Opto-Electron Eng, 51, 240028(2024).
[24] C C Wang, W He, Y Nie et al. Gold-YOLO: efficient object detector via gather-and-distribute mechanism, 36(2023).
Get Citation
Copy Citation Text
Ziran Peng, Siyuan Wang, Shenping Xiao. A solar cell defect detection model optimized and improved based on YOLOv8[J]. Opto-Electronic Engineering, 2024, 51(11): 240220-1
Category: Article
Received: Sep. 16, 2024
Accepted: Nov. 4, 2024
Published Online: Jan. 24, 2025
The Author Email: Peng Ziran (彭自然)